1.0 Introducing the Issues

1.1 Organizational and Social Informatics in System Design

Computer systems have constituted a significant presence in American business,
government, and cultural life for about a third of a century, and with each
passing year they evolve rapidly in technical sophistication, in scope of use,
and in processing power. Despite the extraordinary advances achieved to date, a
tone of concern has developed among the many scholarly disciplines which work
with these technologies. There is widespread agreement that we need new ways of
thinking about computers and information technologies: new conceptions of how
computing fits into larger organizational processes; a better understanding of
how the soft" human systems and skills surrounding the machinery contribute to
the success or failure of the enterprise; improved theories about how
decision-making activities are best distributed between humans and machines,
and how the interior processes of machines can be represented symbolically so
that human operators can really remain in control"; new ways to grasp the role
of information technologies as arteries in vast communication networks of
people, groups, and organizations. These are all major intellectual challenges
for researchers in the years ahead.

Computer scientists, systems designers, and social scientists have come to
realize that our individual intellectual disciplines have become dwarfed by
the complexity, dynamism and scale of today's information technology. Not
only are the largest systems so complex that no individual can fully understand
them or anticipate all their actions, but even those of us who work on
particular pieces of systems have come to understand that to do our work well
we must appreciate and anticipate the interactions of the hardware, the
software that will run on it, the skills and purposes of the people who will
use it, and the organizational and political environment in which the system
is put to work. In other words, the complexity, interdependence and social
embeddedness of modern computer systems are mirrored in the intellectual
challenges which individual researchers face.

Many of us have come to view the intellectual challenge facing us as
envisioning, designing, and researching Human-CenteredInformation
Systems for the next century. This implies a shift in the ways we have
been doing research towards a more inter-disciplinary approach in which the
computer scientists, systems engineers, and social scientists collaborate
together (Bowker, et al., 1997). It differs from past practice in which
computer scientists tended to focus on the development of hardware and
software, and left studies of the actual uses and impacts of their systems (if
any) to social scientists whose research was independent of the originators. In
practice, relatively little social research was carried out on the use and
impacts of computer systems. As a result, many systems which looked wonderful
in a development lab failed to live up to their promise when placed in
real-world settings because their designers did take account of important
social relationships around system users (and others in their workworlds).
Conversely, many systems "work well" because of ways that users tailor them and
work around some of their limitations. Unfortunately, this kind of knowledge
about the nitty-gritty practices of systems use has not filtered back into the
education of systems designers and into a well organized body of knowledge that
practicing designers can readily learn and follow. The promise of
human-centered systems is that knowledge of human users and the social context
in which systems are expected to operate become integrated into the computer
science agenda, even at the earliest stages of research and development.

Fortunately, we are not beginning in total ignorance of relevant principles.
For the last 20 years there has been a growing body of research that examines
social aspects of computerization -- including the roles of information
technology in organizational and social change and the ways that the social
organization of information technologies influence social practices (and are
influenced by them). This body of research is called Social Informatics (and
Organizational Informatics when the focus is upon systems used within
organizations). The names social informatics and organizational informatics are
relatively new. But they are new labels that bring together studies that have
been labelled as social impacts of computing, social analysis of computing,
studies of computer-mediate communication (CMC), CSCW, and so on. (See the
Social
Informatics Home Page) for a listing of research and teaching materials
http://www.slis.indiana.edu/SI)

1.2 Opportunities and Crises in Systems Design

For some, the conclusion that our research agenda must change stems from a
sense of crisis in current system design practice: that there is a lag
in the development of analytical approaches and institutions which can safely
manage the greater complexity of today's information systems, and in a way that
will be more effectively human-centered. For others, the need for change is
demonstrated by spectacular failures of some very large systems which can be
attributed to the combination of human and technological factors: The
Challenger disaster; the failures of air-traffic control systems (Stix, 1994)
and long costly delays in the development of systems for agencies such as the
Social Security System and the IRS; problems with the implementation of
private enterprise-wide information retrieval systems such as SAP/ R3 - are all
examples.

For others, there is less a sense of crisis than one of opportunity to advance
our understanding of computers and communications in human society, and
identify the principles of interactive complexity, human-machine interaction,
and social embeddedness evidenced by state-of-the-art systems. Here are some
examples where technical and social issues are so intertwined in modern
large-scale systems that they need to be examined in an integrated way:

Medical information systems constitute some of the largest and most complex
computer applications in widespread use today. Such systems include insurance
record-keeping functions, as well as diagnostic and patient history
information. In many places, these systems are a kind of collage built out of
separate modules, designed at different times for distinct purposes.
Increasingly, however, the value of such systems, whether for health care
economists, office workers, epidemiologists, or physicians, depends upon the
successful integration and combination of data from all these sources (the
interoperability of the component systems). This goal presents designers and
researchers with tremendous intellectual challenges which are simultaneously
technical and social. Integrating these databases not only depends upon very
fast filing and retrieval algorithms and powerful database software; it also
depends upon overcoming differences in medical classification and nomenclature
systems - understanding the knowledge domains to be represented and then
developing standards. Beyond knowledge engineering, such systems touch on
ethical and privacy issues, from whom should gain access, to what kinds of
personal and group membership information are appropriately stored and accessed
alongside the medical data. The systems also raise usability issues: what kinds
of people are expected to access them, in what kinds of settings. Should they
be designed such that they can be accessed only by technical experts with
substantial training in the particular systems, or are they to be usable by
novices with little training, using simple search tools?

In many businesses, computerized accounting systems appear like the layers of
an archaeological dig, with newer systems built upon older systems, with the
added dimension that large-scale information technology now makes possible the
rapid transmission of this information across traditional organizational
boundaries, as well as building into these systems various workplace
surveillance capacities. There is often no a central rationale or architecture
for these diverse organizational accounting systems, and systems developers,
analysts, managers and employees feel themselves caught in a web of overly
complicated and redundant accounting schemes. Such legacy systems" can take on
a fragile inflexible quality: changing any part of them is fraught with
problems, not only because one is changing archaic code, but also because what
seem to be harmless modifications of one part may prove to have unexpected, and
occasionally disastrous effects on other parts of the system.

The proliferation of such legacy systems is one small part of the productivity
paradox" which refers to the discrepancy between the expected economic benefits
of computerization and measured effects. (See Harris et al., 1994; Landauer,
1995). But the importance of the productivity paradox is not simply anchored in
macroeconomic statistics; the paradox might be resolved by better average
performance of computer systems in leverage organizational performance. Even if
average performance is improved, many managers and professionals can continue
to see information systems whose use fails to improve economic productivity,
and even occasionally becomes a barrier to workplace innovation and
improvement. Solving these problems is not merely a matter of paperwork
reduction. It requires quite extensive mapping of work-task domains,
understanding the interdependency of various computation tasks, mobilizing
cooperation from all parties, and developing shared information standards and
an acceptable system architecture.

One of the problems and scientific challenges we face is a lack of a coherent
theory of human/system complementarity for complex work: what should best be
left to the human operators and what part to the machine, what routines should
be built in so that each participant can check up on or remedy the actions of
the other, how the forms of representation or knowledge-mapping of the machine
should fit with those of the human, and so on. There are theories for special
cases, such as aircraft operations and statistical data analysis. Older models
of human-computer interaction did not model the kinds of scope and scale found
in today's high-complexity systems. As a result, the opportunities for error in
today's systems, and the difficulties in identifying and correcting errors,
proliferate. Further, many of today's computer systems are used to support
human communication. We have little systematic understanding about the role of
face-to-face, telephone, and email in supporting effective communications.

Studies of the routine use and social impacts of computing are just now moving
to understand uses and impacts where such dense and ubiquitous computerization
already exists in an installed base. Most of our conceptual tools were
developed for understanding the automation of individual tasks, and are being
extended to team-wide applications in CSCW studies. Some information systems
theorists have helped us to understand limited aspects of organizational-scale
systems, while modern systems move towards inter-organizational networks and
the computerization of entire industrial sectors.

The problem of standards is central to both legacy systems and the development
of new systems and protocols. Within the Internet, for example, there are more
than 100 accepted standards, and more on the table being reviewed. Attention to
the problems of standardization has been relatively sparse, given the magnitude
of the problems spawned by mismatches and proliferation of standards. There is
both a need and an opportunity for a joint social, organizational, and
technical analysis to understand the prospects for effectively developing
various kinds of standards.

The ease of use of computers - usability - remains a critical issue, in part
because ordinary users embrace ever more complex and larger-scale applications.
Email, once the province of a small world of computer scientists and engineers,
is rapidly becoming commonplace. Active professionals are experiencing email
overload, and good social conventions for filtering, pacing, and even
discarding email, are lagging behind the growth of mail (Yates and Orlikowski,
1992; Kling and Covi, 1993). At the same time, the Internet itself, including
commercial carriers such as AOL, groans under the traffic and backs up. The two
phenomena together threaten a kind of email gridlock, with deleterious
consequences for individual and social productivity.

This state of affairs offers us the possibility of understanding emerging
communications conventions, of action research into the dynamics of the
network, and of understanding the role of email in the work process. It raises
a host of intriguing research questions, from the role of trust in electronic
communication, to the conditions for sharing versus hoarding knowledge, to the
spill-over effects of shared information (Kraut and Attewell 1997) to the role
of electronic communication in drawing peripheral members of organizations
closer into the mainstream (Sproull and Kiesler, 1991)

A similar situation exists with proliferation of information on the Internet or
World-Wide Web. Many social, information, and computer scientists are
interested in better indexing, cataloguing, and filtering mechanisms for the
information found on the Web.

2.0 When Should Computer Systems be Called Human Centered?

We began our group discussions by examining the term "human centered" and
tried to characterize it clearly. We were specially concerned that the term
"human centered" could easily become a trivialized buzzword that could casually
be slapped as a label onto any computer application that seemed to help people.
We did not believe that certain kinds of applications, such as medical
diagnostic aids, should be automatically be called human-centered because
improved medical diagnosis can help people. For example, a medical diagnostic
system whose logic is difficult for a doctor to comprehend or interrogate would
not be very human-centered.

Thus, we spent considerable time answering these questions:

What are the meanings of human-centered that justify a new label? What
research questions would there be? What do we know about the organizational
and social aspects of computer systems that sheds light on human centered
systems developments? The following paragraphs summarize our deliberations.

There is no simple recipe for the design or use of human-centered computing.
Our group agreed, however, that the analysis of any aspect of systems should
take into account at least four dimensions of human-centeredness:

1. There must be analysis which encompasses the complexity of social
organization and the technical state of the art. The analysis cannot be based
upon a vague idea of what a generic individual would like, sitting at a
keyboard in social isolation or in a stereotypic situation that effectively
ignores the varieties of concrete social locations.

The computing world has developed a number of such generic scenarios, such as
4A -- in which any one can get any document anytime and anywhere. There are
instantiations of 4A -- such as providing any researcher all of the
documentary materials that they want for their research, even if they are
traveling for a month; or providing any doctor with a complete medical record
for any patient, anytime, anywhere. We can appreciate the practical value and
symbolic power of these crisply stated goals. But they too easily trivialize
the concept of human-centered system by homogenizing people and places into
"everyman" and "everywhere." The various roles that people play in work groups
are ignored and stereotyped. The ways that organizations structure information
is also treated only as a barrier, unless materials are accessible 4A. The
different kinds of resources (and skill sets) of organizations and groups are
also all homogenized in 4 A scenarios.

In contrast, a human centered analysis must take account of varied social units
that structure work and information -- organizations and teams, communities
and their distinctive social processes and practices.

2. Human-centered is not a "one-off" or timeless attribute of a system at a
given point in time. Rather, it is a process, one which would take into
account how criteria of evaluation are generated and applied, and for whose
benefit. It would include the participation of stakeholder groups -- such as
involving patient groups in the development of specialist medical technologies,
or teachers in the development of instructional technology.

3. There are important architectural relationships, such as the question of
whether the basic architecture of the system reflect a realistic relationship
between people and machines. As with the architecture of buildings, the
architecture of machines embody questions of livability, usability and
sustainability.

4. The question of whose purposes are served in the development of a system
would be an explicit part of design, evaluation and use. Thus the question of
whose ideas get put into the design process is an important one for human
centered systems. As well, the question of whose problems are being solved is
important -- systems which seek only to answer a very narrow technical or
economic agenda or a set of theoretical technical points do not belong under
the "human centered" rubric.

2.1 What is and isn't HCS

There is no single recipe for human centered design. Given that humans
are so diverse, by nature human centered designing tends to be tailored, rather
than mass produced. "One size fits all" seems distinctively non human-centered.
On the other hand, we don't believe that complete tailorability results in
human centered systems, because few people have the time or interest to
effectively learn how to tailor thousands of features in complex computer
systems.

The question of what is and isn't HCS may be divided into four parts:

1. What do we mean by human?

2. What is a system?

3. What are the goals of a human-centered system or process?

4. What are the processes associated with HCS?'

2.2 What do we mean by human?

We use the word human to mean a person with activities who participates in
some workworlds, communities outside of workplaces, and a lifeworld. We don't
use the term human to refer to a disembodied task, or to a set of cognitive
processes. Humans are not divisible up into component parts such as tasks.
Thus, a design which optimizes for performance of a data-entry task but which
does not take into account ergonomics, organizational reward structures, and
the other tasks, activities and feelings a person brings to the job is not
effectively taking the human into account.

People are not stand-alone organisms -- we are quintessentially social and
collective, not just individuals -- or individuals in a diffuse social world.
We do not use the term "human" to refer to individuals working alone or to a
set of cognitive activities. For use, the term human includes and goes beyond
individuals and their cognitions to include the activity and interactions of
people with various groups, organizations, and segments of larger communities.
Thus, for example, we would view the appropriate communication systems to
support distance education to be those which students to communicate with
instructors and with each other, and not simply to download files and upload
from an instructional site. Further these systems should be organized in ways
that fit students' lifeworlds (ie., not require forms of connectivity that
students could not sustain at home) and also enable communicants to develop
some knowledge of and trust in each other.

People adapt and learn, and from the point of view of systems design,
development and use, it is important to take account of the adaptational
capabilities of humans (Dervin, 1992). Something that freezes at one
development stage, or one stereotyped user behavior, will not fit a human
centered definition.

Finally, it is worth noting that human systems are just as complex as
technical systems (if not more so!). That is, although there is often a
"it's common sense" approach to defining what is human and what human problems
and challenges should be, the answers are no less complex than building a
highly complex technical system.

2.3 What is a (more) Human Centered System?

Having characterized the meaning of "human," we can then better
characterize human-centered systems?

First, design predicated on merely replacing human activity or automating is
not human centered. That is, systems which do this may be interesting, but are
not per se human centered -- in fact they may act to the detriment of humans in
particular situations.

Human-centered systems are designed to complement humans skills. The impetus
to build such systems are based on human needs, for information, assistance, or
knowledge. We recognize that the conditions under which people use such systems
vary considerably. An aircraft navigational system might remove significant
control from a pilot and use a logic that is difficult to explore when a plane
is flying at 200 mph near ground and other planes. In contrast, a medical
diagnostic system might have to be designed so that a doctor can examine how it
weighed evidence and a rule-base to make a specific diagnosis.

HCS designers recognizes that computer systems structure social relationships,
not just information. (For example, email systems that order messages for a
person to read based on criteria such as recency or length also influence the
recipients' social relationships by encouraging attention to some messages and
their senders rather than others). So the analysis which informs design is not
just about optimizing the technical capacities of the machines, but also
recognizes and respects the organizations or other forms of human social
organization (such as the family or the classroom) into which they are being
inserted.

HCS design should take into account the various ways that actors and
organizations are "connected together" with social relationships, as well as
information flows and decisional authority. For example, changes in a
classroom may produce changes in the students' families if children encounter
new opportunities to explore ideas freely. While we can't predict all such
outcomes, human-centered systems designers should be cognizant of the
possibility via analysis of systems' use in some very realistic contexts.

2.4 What goals best describe a human-centered system or process?

The holistic attitude of Human-Centered systems designers toward a person and
their lifeworld is important. Since people are not reducible to a set of
component tasks taken out of context, the strategies of Human Centered Systems
design -- and technologies to support them -- should reflect this complexity.

There are two senses of the term "ecology" that illustrate this (Star, 1995b).
The goals of a human centered system (or process) would be ecological in the
sense of accounting for the larger picture of systems development and use.
For example, displacing work does not make it go away. A system which is used
to replace all the secretaries in a firm, while requiring extra hours of other
employees to make up for the loss of services, has not accounted for the real
organization of work. Fuller (1995) coined the term "cybermaterialism" to refer
to the analytical approach in which the analyst is specially sensitive to the
ways in which computerization reorganizes work and costs rather than simply
reducing or eliminating them. As well, there are larger scale issues of
infrastructure development, ethics and humaneness which are important; for
example, the Computer Professionals for Social Responsibility guidelines for
NII development suggest ethical as well as ecological approaches to
infrastructure development that clearly have a place in discussions about
human-centered computing (http://www.cpsr.org/cpsr/nii_policy).

Human Centered System designers would also ideally be ecological in terms of
global concerns, and take into account issues of environmental sustainability.
In this, by implication, we do not necessarily accept that only humans
are important. A system which monitors acid rain or tree disease has wider
natural implications as well.

The goals of a human centered system are not fixed once and for all, and then
good for all contexts. People who user systems must be able to help define
what they need systems to do (usually); it certainly means not just testing
design when one is well down the design path, after it is too late for good
user feedback. In this, we see a desirable shift from passive users of systems
to more active participants in systems at all developmental phases.

Human Centered System designs must also scale up to become non-trivially human
centered, and often here the values and implications for impacts change
significantly. What works for a small group in a laboratory may entail larger
scale issues which look different -- for example, privacy changes a great deal
with larger groups, with lack of face to face accountability, and as systems
move from the lab to the real world (Clement, 1994b). In this, the goals of
human centered systems design should be congruent with social sustainability as
well as environmental sustainability; analysis of policy and political
implications especially with scale are important to defining a system's goals.

Finally, the system designers should use the best available social science
knowledge in addressing all of these above points. Interdisciplinary teamwork
is crucial to making this practice workable.

2.5 What are the processes associated with design, use and analysis of
HCS?

How does one design, use and analyze human centered systems, according
to the above precepts? Our group recommended several foci, including but not
limited to the following:

a. One should take cognizance of multiple media (paper, computing, video,
conversation, etc.) in the process of design. That is, information systems are
always part of a large ecology of communicative devices and conventions,
ranging from conversations to faxes and post-it notes. The interaction of these
media is important for understanding the big picture of design in a human
centered sense.

b. Human centered analysis would also extend to infrastructure and standards.
That is, the usability of a system depends on infrastructural configurations of
all sorts. Computers sent to a developing country without knowledge of the
problems with its power grid and the dust-filled atmosphere may fail for
reasons other than pure design; systems which work well for one group but
violate existing standards in use for another will also not work.

c. Technology does and will not solve social justice problems. For example,
putting more computers into inner city classrooms will not per se increase
literacy. This is important to a human-centered approach, as is a certain
modesty about systems capabilities. Sometimes "less is more", and the system
which is helpful as a tool in solving a particular problem may not always be
the most elegant technically. From a human centered perspective, 'pretty good
systems' are sometimes the best systems.

d. Another part of human centered designing is articulating the values that are
at stake in design processes themselves. This means examining the values of
both designers and of the intended systems audiences and also being able to
identify value-conflicts. This is only partly managed by user participation;
it also requires ethics and values analysis for which it may be valuable to
involve professionals who are very skilled in analyzing social values and
social change.

e. Finally, in the design of human-centered systems, machinery should not be
anthropomorphised. Machines should extending human capability as gracefully
as possible. In line with the value of not simply replacing humans,
human-centered system designers must know the limits of machines in a specific
social order, and not impute certain human properties to them, such as fairness
or objectivity.

3.0 State-of-the-art

We identified a body of research that is fundamental for anyone who wishes to
understand how human centered systems can help or hinder organizations and
social groups. In this brief review, we separate the research into five
categories: evaluation and usability (including user centeredness); problems,
paradoxes and overlooked social realities; organizational and group and
community processes; co-design and design issues; and infrastructure, person
power and training.

3.1 Evaluation and Usability (including user centeredness)

There is a large body of research on the evaluation of systems, interfaces,
and usage at the individual level (see e.g. Bishop and Star, 1996; Hewins,
1990). Task analysis -- an individual system user and her tasks -- are also
well understood. However, human centered systems have to be workable for
groups. Some recent research has begun examine these issues at the group,
organizational and community levels.

3.2 Problems, Paradoxes and Overlooked Social Realities

Much of the research about the social and organizational aspects of systems
has pointed out actual and potential problems with design and use. In broad
brush strokes, these include the following topics:

1. Computerization is ongoing, along with other organizational processes,
rather than one-shot.

The computerization of common organizational activities, such as accounting,
inventory control, or sales tracking, is not a one-short venture. Computerized
systems that are introduced at one time are often refined over a period of
years (Kling & Iacono, 1984), and periodically replaced by newer systems.
Some computerized accounting systems have histories of 30 or 40 years (McKenney
and Mason, 1995), and 10-20 years is quite common in manufacturing.

The decade-long time frame for the life of many computerized systems makes
their adaptability to changing working and operational conditions an important
aspect of human-centeredness (Zmuidzinas, Kling, and George, 1990). However,
adaptability alone is not a sufficient condition for an information systems to
be human centered. Software AG's SAP R/3 Enterprise Integration system is an
interesting case in point. SAP requires that standards be set across an
organization, but also allows many parameters to be tailored. Many large
firms, including Corning, Compaq, Chevron, Borden, Owens-Corning, Mentor
Graphics, Fujitsu, Dell, Apple, IBM and Microsoft are using SAP to help
integrate far flung operations. It is common to have 8,000 data tables in an
SAP database (Xenakis, 1996), and it is easiest for firms that have high levels
of administrative centralization to decide upon parameters for geographically
decentralized operations.

Because the customization is very complicated, some firms restructure the way
that their people work and even their business policies rather than completely
tailor SAP's R/3 (White, Clark, and Ascarelli, 1997). SAP is not a
"human-centered system;" it is a strong example of an "organization centered
system" that makes exceptional demands upon people to use it effectively. SAP
is an interesting contrast to the kinds of Human Centered Systems (and design
principles) that this research program should promote.

This discussion breaks new ground because we know relatively little about the
conditions under which computer systems that are very human-centered also
provide strong organizational support, and vice versa. Some readers have been
surprised by our treating organizational-centered and human-centered systems as
potentially very different. In our view, we will make more research headway by
not automatically identifying human-centered with organizationally-centered
(any more that we would say that all organizational structures and practices
are always good for an organizations' employees, clients, etc.)

2. Neither technical excellence or market share alone define system
survival. "Network externalities," on the other hand, can play a substantial
role in the sustainability of system.

Economists have demonstrated the "path dependencies" associated with technical
standards (Antonelli 1992). The analysis of these effects was inspired partly
by the economics of telecommunications systems, in which subscribers often have
an economic incentive to connect with the largest network (Cristiano, 1992).
Computer users, likewise, often have economic reasons to adopt the dominant
standards in information technology, even in cases where another standard might
be preferable on narrow technical grounds. This phenomenon has profound
consequences for the dynamics of competition in IT markets (Farrell and Saloner
1987), and consequently for policy as well (Kahin and Abbate 1995).
Standardization also has broader economic consequences; research on business
information (Bud_Frierman 1994; Bowker, Timmermans and Star, 1995), for
example, has pointed to the mutual reinforcement between communication
technology (which allows information to be transferred from dispersed locations
to centralized offices), information technology (which increases the incentive
to centralize information by making it easier to process), and the
standardization of products and practices (which makes the various elements of
accumulated information commensurable). The resulting economies of information
ought to have pervasive consequences, although the nature and magnitude of
these consequences remain controversial (Babe 1994).

Operating systems, such as UNIX or Microsoft Windows, were not necessarily the
technically best alternatives when they were widely adopted. However, each of
them was part of a larger matrix of social/technical systems and resources.
UNIX was distributed as an "open system" to academic computer science
departments whose technically inclined students were able to enhance it, and
who sought it in the engineering labs and product development firms that
employed them after graduation.

Microsoft Windows was, in some ways, technically inferior to IBM's OS/2. But
the set of software companies that were willing to support Windows vastly
outnumbered the number of firms that were willing to support OS/2. Neither of
these observations about UNIX or Windows means that they were "poor
technologies." Rather, we are noting that technologies become popular for
reasons that are sometimes quite different from their technical strengths and
weaknesses. Conversely, technologies can fall in popularity because of
declining network externalities. For example Windows 95 is not quite as refined
as the Apple Mac operating system; but Microsoft has out-marketed Apple in ways
that lead software developers (and then the market) to shift away from Apple.

In a similar way to UNIX and Windows, SAP /R3 (and its enhancements) may
become a commonplace Enterprise Integration system because of externalities,
such as the extent to which consulting firms recommend it (White, Clark and
Ascarelli, 1997) and offer training to help firms adopt it and tailor it.

3. There is a significant gap between the productivity that should result
from the nation's investment in computer systems and the actual productivity
gains in the economy.

The discrepancy between the expected economic benefits of computerization and
measured effects has been termed "The Productivity Paradox," based on a comment
attributed to Nobel laureate Robert Solow who remarked that "computers are
showing up everywhere except in the [productivity] statistics."

Many analysts have argued that organizations could effectively increase the
productivity of white collar workers through careful "office automation".
There is a routine litany about the benefits of computerization: decreasing
costs or increasing productivity are often taken for granted. In the last few
years economists have found it hard to identify systematic improvements in
United States national productivity which they can attribute to
computerization. Although banks, airlines and other United States service
companies spent over $750 billion during the 1980s on computer and
communications hardware __ and unknown billions more on software __ standard
measures have shown only a tiny 0.7 percent average yearly growth in
productivity for the country's service sector during that time. (Productivity
growth in many sectors of the United States economy was much lower since 1973
than between the end of World War II and 1973.)

In the mid-1990's, US National productivity has been closer to 2-3%/year. Macro
economists see this as a workable growth rate, but it has also lead to income
stagnation for many middle class families. It is also tiny relative to the
25%/year improvements in the cost/performance of computer hardware.

Research identifies many common social processes which reduce the productivity
gains from computerization. Many changes in products and ways of work that come
from computerization, such as improving the appearance of reports and visual
presentations or managers being able to rapidly produce fine grained reports
about their domains of action, often do not result in direct improvements in
overall organizational productivity. Numerous accounting reports may
give managers an enhanced sense of control. But managers may seek more reports
than they truly need, as a way to help reduce their anxieties about managing.
(SAP /R3, for example, can provide rapid access to transaction level detail
about operational activities in diverse divisions of a multinational firm; a
manager in San Jose California can readily track daily inventories in Munich
and Melbourne).

Similarly, some professionals may be specially pleased by working with advanced
technologies. But much of the investment may result in improving job
satisfaction rather than being the most effective means for improving
organizational productivity.

There are good diagnoses of the productivity process (and paradox) with respect
to linkages between individual and organizational scale behavior (but not yet a
clear solution)(See Harris et al., 1994; Landauer, 1995; Attewell, 1996).

4. Workable computer systems are usually supported by a strong
socio-technical infrastructure.

The "surface features" of computerization are the most visible and the primary
subject of debates and systems analysis. But they are only one part of
computerization projects. Many key parts of information systems are neither
immediately visible or interesting in their novelty. They include technical
infrastructure, such as reliable electricity (which may be a given in urban
America, but problematic in many Third World countries, in wilderness areas, or
in urban areas after a major devastation.) They also involve a range of
skilled-support -- from people to document systems features and train people to
use them to rapid-response consultants who can diagnose and repair system
failures. System infrastructure is a socio-technical system insofar as
technical capabilities depend upon skilled people, administrative procedures,
etc.; and social capabilities are enabled by supporting technologies (i.e.,
word processors for creating technical documents, telephones and pagers for
contacting rapid-response consultants).

Much of the research about appropriate infrastructure comes from studies of
systems that underperformed or failed (Star and Ruhleder, 1994; Kling and
Scacchi 1982). The social infrastructure for a given computer system is not
homogeneous across social sites. For example, the Worm Community System was a
collaboratory for molecular biologists who worked in hundreds of university
laboratories; key social infrastructure for network connectivity and (UNIX)
skills depended upon the laboratory's work organization (and local university
resources) (Star and Ruhleder, 1996). Star and Ruhleder found that the Worm
Community System was technically well conceived; but it was rather weak as an
effective collaboratory because of the uneven and often limited support for its
technical requirements in various university labs. In short, lack of attention
to local infrastructure can undermine the workability of larger scale
projects.

There is a small body of research that amplifies these ideas. Web models of
computing (which are not related to WWW) treat the infrastructure required to
support a computerized systems as an integral part of it (Kling & Scacchi,
1982; Kling, 1992).~Star and Ruhleder (1996) have also shown that there are
subtle individual and organizational learning processes underlying the
development of local computing infrastructure (including the ability of
professionals with different specialties to communicate about computerization
issues) (see also Star, 1995b; Ruhleder, 1995 ).

3.3 Organizational, group and community processes

There is a solid body of empirical and theoretical work which identifies a
variety of processes at scales above the individual. Among the points made in
this research are the following:

1. Information sharing in groups can be supported by computerized systems,
but organizational incentive systems play a major role in influencing the
extent of information sharing.

One of the capabilities enabled by shared databases is the possibility of
groups sharing data/information that was previously inaccessible in a timely
manner, if at all. It is easy to identify examples, such as airline reservation
systems where shared databases of seats on flights enhance the quality of
service to passengers and the operational efficiencies of the airlines.
Information sharing is technologically enabled by most computerized information
systems; and some systems attract managers and professionals because of new
kinds of information sharing that they enable. (For example, SAP /R3, as
discussed above, can provide rapid access to transaction level detail about
operational activities in diverse divisions of a multinational firm. Intranets
seem to becoming popular for enhancing the flow of certain information across
the boundaries of organizational subunits).

Much of the value of groupware applications, such as Lotus Notes, hinges on the
promise of professionals' sharing narrative materials -- such as client studies
in multi-office consulting firms, country-specific market-intelligence in
multi-national firms, and software bug fixes in a vendor's technical support
office. Careful research finds mixed support for the value of these
applications (Orlikowski, 1993; Orlikowski, 1996, Ciborra and Suetens, 1996).
Each of the studies just cited found some examples of Lotus Notes' use, but
only staff in the technical support office made extensive use of Notes for
routinely sharing information. In many consulting firms there is a negative
incentive for consultants to share reports; they are rewarded for the time that
they can bill to their clients and -- to some extent -- for demonstrating
unique expertise (Orlikowski, 1993). Managers at a French (national) public
utility company had hoped that their staff would use Lotus Notes to share
information about market conditions, but they did not alter their
organization's reward system to compensate for the time involved in creating
online reports. While a pilot group was highly enthusiastic to share
information via Notes, the project "lost momentum" as other groups were asked
to participate (Ciborra and Suetens, 1996). In contrast, a small technical
support workgroups in which technicians helped each other with problem call
before they used Notes, found Notes to be a helpful extension of their
preexisting cooperative practices (Orlikowski, 1996).

2. People who use computerized systems are often using multiple media.

Much of the writing about computerized systems tends to focus on the digital
media that is part of the official systems design. But we know that people also
other media, such as paper and telephone, as part of their work. In the case of
digital libraries, some analysts take notes on paper about materials that they
find on-line (Levy and Marshall, 1995). Scholars who read electronic journals
often print out long articles onto paper for sustained reading and markup
(Kling and Covi, 1995).

In an intriguing kind of example, air traffic controllers use paper "strips"
for key information about flights in their sectors; and to share it when they
pass control over an aircraft to a colleague (Stix, 1994). Stix (1994) article
reports that recent efforts to develop a completely electronic flight control
system lead to efforts to replace paper strips with unwieldy databases with
dozens of fields.

3. The routine use of computer systems often requires articulation
work

The concept of "articulation work" characterizes the efforts required to bring
together diverse materials or to resolve breakdowns in work (such as clearing a
paper jam when printing a long electronic document to read). In a provocative
study, Gasser (1986) found that anomalies were common in many use of computer
systems, and that professionals often developed informal (and sometimes
strange) workarounds to compensate for recurrent difficulties. Suchman (1996)
observes how articulation work is often invisible to people who are not close
to the place and moment of working. She also notes that articulation work can
require notable ingenuity, but that higher status professionals (and managers)
who are buffered from the details of computer work, tend to trivialize the
nature of the work to be done. To the extent that high status professionals and
managers who can delegate most of their work to others are male, and that many
of the clerical and technical staff who do the work are female, there is also a
gender politics to articulation work. But Schmidt and Bannon (1992) argued that
articulation work is so pervasive that (humanly) effective system designers
have to routinely examine how new systems reduce, increase, or reorganize
articulation work.

4. It is critical to comprehend the use of many computerized systems in
terms of specific social units, such as workgroups, teams, local communities
and communities of practice.

It is common for systems designers to conceptualize computerized systems in
terms of organizations and individuals ("users"). But there are important
intermediate levels of social organization between individuals and the larger
collectivity. In practice, workgroups and teams (Galegher, Kraut and Egido,
1990; Ciborra, 1996; Tyre and Orlikowski, 1994) have proven to be critical
social groupings which shape the use of computerized systems. (See below for
some examples).

Brown and Duguid (1991) coined the term "communities of practice" to refer to
people who are concerned with a common set of work practices. They are not a
team, a task force, and not even necessarily an authorized or identified
group. People in CoPs can perform the same job (but work in different places
much of the time, such as field service engineers), collaborate on a shared
task or work together on a product. They are peers in the execution of "real
work." What holds them together is a common sense of purpose and a real need
to know what each other knows. There are many communities of practice within a
single organization and most people belong to more than one of them. Some
research shows that communities of practice are the appropriate groups for
learning how to best integrate new computer systems into real working practice
(George, Iacono & Kling, 1995; Jones, 1995).

Local communities, as well, can be important units of analysis and frames of
reference for human centered computing. "Community information systems" may
mean organized information provision to special constituencies (e.g. cancer
patients, small business owners, hobbyists), or it may be geographically local
provision of services, including freenets and other public computing
facilities. For more information on this, Prof. Ann Bishop has offered to
share her syllabus from the University of Illinois for a graduate class,
Community Information Systems
(http://alexia.lis.uiuc.edu/gslis/courses/syllabi/450CI.html).

5. Communication is a key value for many users of computer system (even
where that has not been an explicit or high priority goal).

For example, email was the "killer application" that drove up the use and
demand for the Internet (in contrast with file transfer). Bullen and Bennett
(1996) found that email was the most frequently used application within
workgroups that used office suites that included group support functions (such
as calendars).

6. There is an understanding of emergent social psychological processes when
individuals work together in groups with computer networks

Social processes in groups that use electronic mail have been the subject of
substantial research. We understand that email can reduce the contextual cues
in messages (Sproull and Kiesler, 1991), and that flaming can result as a
byproduct of people misunderstanding other's intentions. We also understand
that people's who have on-going work relations can be very cognizant of social
norms beyond those of the electronic workspace, and that these norms can reduce
the frequency of phenomena such as flaming (Lea, O'Shea, Fung, and Spears,
1992). In some workplaces, people use email quite strategically (such as to
convey bad news (Markus, 1994). There have been some systematic studies of the
dynamics of groups online (see Sproull and Kiesler, 1991 for an introduction).
One important finding is that email can gives greater visibility to "peripheral
workers" -- those who are lower in social status, who work in distant location
or in different time schedules that the more mainstream workforce (Sproull and
Kiesler, 1991;, Hesse, Sproull, Kiesler, and Walsh, 1993). There is as well a
related important body of work on scholarly communication which represents
similar processes (Doty, Bishop, and McClure, 1991).

7. Information technologies may become a means of constructing and exploring
individual, group, organizational and community identity.

Communication is not simply a matter of exchanging information. Studies of
on-line communication show that people use them to construct certain identities
(i.e., local technical expert), and in some cases, to explore new social
identities (Mantovani, 1996).

3.4 Co-design and design issues

A more recent development in this research area is the partnership of social
and computer scientists, particularly the participatory design or co-design
thrust. Some findings from this area:

1. Designers design both system and shape the setting

The separation between system and setting can seem simple -- the system is the
computer system (and telecommunications) and the setting is the arrangement of
furniture, lighting, walls, and other facilities. In some cases, such as the
design of cockpits and control rooms, teams explicitly design both system and
setting. In other case, people reorganize their offices to more comfortably
use computer systems -- pulling down venetian blinds to reduce glare on
computer screens, shuffling desktop materials to make room for monitors and
printers, and so on. In both cases, computerization reshapes the use of space
and the ways that people inhabit it.

Some of partnerships have been pioneered in Scandinavia (Kyng and Greenbaum
1991; Clement and Van den Besselaar, 1993; Bødker and Grønbaek,
1996), but they have also been developed within major North American firms,
such as Xerox and NYNEX (Euchner and Sachs, 1993; Clement, 1994a). Dutton and
Kraemer's early work on negotiations about computer modeling also points to
complex de facto processes of implementation, modification and the politics of
design (1984).

3.5 Infrastructure, community, personpower and training.

In the past few years the scientific community of those who study social
impacts of computing, design, and social theory in information technology have
created a scientific community in social Informatics. This has included the
development of

1. Scientific journals

Information Systems Research

Journal of Computer Supported Cooperative Work

Office: Technology and People

Accounting, Management and Information Technologies

The Information Society

2. Conferences

Organizational informatics research is routinely discussed at a few annual
conferences (International Conference on Information Systems, Association for
Information Systems), the biannual conference on "Computer Supported
Cooperative Work," and periodic conferences of certain IFIP Working Groups,
such as WG8.2 (Information and Organizations). Social informatics research is
not routinely discussed at these conferences or other identifiable conferences,
although social informatics research is discussed infrequently at numerous
conferences in various fields.

* in the graduate programs of a few North American computer science programs
(ie., UC Irvine) and many European CS Departments (especially in
Scandinavia).

Social informatics courses are most often taught in undergraduate Computer
Science programs and in the graduate programs of Information
Science/Information Studies schools. (See the Social
Informatics Home Page for
a listing of courses and degree programs.)

We believe that both organizational informatics courses and social informatics
courses should be much more widely available to computer science students (at
all levels). In addition, the PhD education of prospective faculty would be
strongly enhanced through NSF traineeships in organizational and social
informatics.

4. Research Funding

The most sustained -- but very limited -- research funding for this nascent
area has come from the NSF (especially IRIS). One-shot research projects have
been funded by other foundations including the Annenberg Foundation, the Getty
Foundation, and the Markle Foundation. Unfortunately, funding is spotty, so
that even good senior investigators do not routinely have a continuing stream
of extramural research grants.

In addition to the topics under state of the art, we also identified instances
of projects and practices where social scientists have contributed to human
centered systems developments. There is a new (small) group of scientists who
specialize at the intersection of social/organizational analysis and technical
systems development. The following list identifies a few of the many different
ways that social scientists and computer scientists have collaborated
effectively on systems design/development projects.

* Fieldwork in support of requirements analysis. Fieldwork in settings in
which systems development and work with computer systems will be done (see
Forsythe, 192, Forsythe, 1994; Wagner, 1993).

* Joint project teams with social scientists and computer-scientists. The
Home-net research project at CMU illustrates a project that was investigator
initiated but whose instrumentation requirements made the involvement of
computer scientists central.

* Troubleshooting in anticipating political and conflict situations that can
sabotage system use.

* Identifying factors that influence the success and failure of systems
through the post hoc evaluation of complex systems in actual use by the people
and groups that use them.

* Identifying how the seeming intractability of recurrent technical problems is
a symptom of ignoring the social elements in practices for designing,
organizing and using systems.

* Do foundational analysis to conceptualize how people work with, through, and
around computer systems (i.e., Orr, 1996; Kling and Scacchi, 1992).

4.0 Future Research Directions

We identified several areas for further research: distributed
human-centered information systems; representations; attentional economics; the
provenance and quality of electronic documents (Bates, 1986); contextual
knowledge; and the relationship between naturalistic and formal information
systems. It is worth noting that these areas are in flux, as is the entire area
of human-centered computing. Therefore in any of these areas there ideally
should be a combination of action-oriented research, basic research, and
foundational exploration.

4.1 Characterizations and Theories of Human-Centered Systems

In section 2.0, we discussed meaningful conceptions of the term "Human-Centered
Systems." If the concept, Human Centered Systems, is to be the central concept
of a major research program, then it is essential for there to be meaningful
characterizations of the concept that are grounded in the experiences of people
and organizations in working with computerized systems. HCS is not a completely
new phenomenon -- this label better characterizes some systems design practices
and systems developments than others. We need studies of systems in use that
help the research community understand HCS in practice.

A Theory of HCS would link such systems to important human experience and
social/organizational practices -- such as improved communication, easier
work, better quality jobs, and so on. These kinds of outcomes are not
simply deterministic byproducts of using computer systems -- however good (or
human-centered) their design. Research shows that the outcomes of
computerization emerge from the byproduct of ways of organizing, social
practices and the use of specific systems. We need comparable research about
HCS. A first priority is to develop strong empirically grounded Theories of HCS
to help guide developments in this area.

4.2 Distributed human-centered information systems.

Perhaps no term has been more used (and abused) than that of "community" in the
context of widespread use of the Internet. Recent years have seen the
dismantling of much of the centralized mainframe data processing model of
computer usage, in favor of distributed, desktop and networked usage. A key
insight is that distributed systems are not simply technical artifacts, but are
also distributed social systems as well.

This distribution has had a number of consequences, including extreme
permeability of organizational boundaries and the shuffling of memberships
across traditional institutional borders. For example, systems administrators
in (different) large organizations may have more to say to each other than they
do to their colleagues in other departments. It has always been true that
technical specialists often have more in common with each other than with
managers in their own organizations(see e.g. Strauss, 1978). But large scale
distributed computing accelerates the process and provides and opportunity to
support communication across communities of practice. (See Section 3.0 for a
discussion of communities of practice).

One of the touchstone concepts associated with phenomena like these is the
notion of "collective cognition." It is easier to conceive of problem-solving
across group and organizational boundaries, and even to see thinking itself as
a distributed phenomenon, under these new conditions. That is, the ability of
any individual to work professionally is more a function of their participation
in communities of practice that help them in key moments, than in simply their
"individual cognitive capacities." Supporting these understandings includes
sensitivity to semantic differences, processes of cooperation, and the
identification of divisions of labor and differentiated roles within
distributed groups. The key research issues for HCS include effective
strategies for designing distributed systems that are workable for different
groups; and ways to have communities of practice effectively support
distributed systems.

4.3 The organization of effective groups and communities with electronic
support

The word community is often abused in discussions of social life, but it still
retains important meanings and resonances. A group can be called a community
to the extent that its participants feel some sense of mutual obligation and
reciprocity in helping one another, and value their social ties. In the last
decade, thousands of work, public interest, leisure and service groups and
numerous professional and academic communities have tried to use computer
networks to support some of their activities. These efforts have had varying
levels of success; and have been most valued when group or community
participants could not otherwise make contact or meet.

The most visible successful cases are the public Usenet groups (such as
comp.human-factors) and professional listservs (such as ASIS-L). These cases
are successful insofar as some people use them routinely, and they visibly
enhance communication between many of their participants. There are also
significant experiments to use similar collections of electronic forums to
enhance community life in certain towns and cities. The most famous in North
America may be the Blacksburg Electronic Village (BEV), which is sponsored by
Virginia Polytechnic University.

Unfortunately, there is little systematic research and effective theorizing
about the strengths and limits of electronic forums, and ways to improve their
abilities to enhance the social worlds that support them (through funding,
volunteer work, etc.). For example, it is well known that most readers of large
public forums electronic forums such as comp.human-factors or ASIS-L (and
probably BEV) are lurkers who never speak up publicly (by posting) in the
electronic forums.

Supporting geographically distributed groups with electronic means requires
more than simply "putting them on a computer network" or computer conferencing
system. Participants have to be able to trust each other's fairness, and the
relative privacy of each electronic forum, to discus controversial issues
openly. The fluidity of work and professional practice across organizational
boundaries, makes it important to understand the permeability of groups -- how
people and tasks flow across traditional organizational and community
boundaries. It is very easy for comments that people make in one electronic
forum (and in the context of a specific discussion) to be reported elsewhere in
a different (and problematic) context.

Concretely, this may appear as confusion about the boundaries of
responsibility; problems with "freeloading" across electronic boundaries; as
opportunities in the matrixed and networked organization for more efficient
tapping of expertise and gossip, and a recognition of the complexity of human
skills which cross multiple group boundaries. It also requires strategies (or
social protocols) for developing trust of various kinds (including ways of
resolving conflicts and respecting informational privacy) among participants.

Even within organizations, electronic groups provide a challenge for management
and for working people's sense of their tasks and scope of responsibility.
Culturally, does participation in extra-organizational working groups "count"?
How much does service to an electronic community count in the large
organizational reward structure?

Since many professionals are members of multiple groups and sub-groups, a
simple one-to-one mapping between person and group breaks down quickly. Are
there strains involved in managing group memberships? For example, if someone
has technical expertise in the design area, and also works part time as a
design consultant for the organization's marketing group, are the different
goals and norms of the two groups going to produce an irresolvable strain for
the person? How will they juggle conflicting demands? This becomes important
from the systems design and use perspective if support of electronic
communities is a goal -- there must be a means of acknowledging multiple
memberships.

How such groups organize and stay organized is an open research question.
There has been some interest in "mapping cyberspace," and a few studies of the
operation of Usenet discussion groups and emergent web communities.
Nevertheless, from the basic scientific point of view, we know very little
about the dynamics of membership, stability, and overall impact on
organizations (of various sorts). There may be both centripetal and
centrifugal forces at work as groups form and re-form, and these are worthy of
investigation. Total fluidity is not always the best thing from the point of
view of social organization; indeed, boundaries and barriers may help build
group solidarity, and at the least, respect for these basic social processes is
important to inform HCS design.

4.4 Productivity paradox

As we noted above, there is likely to be no single answer to resolving the
productivity paradox. A plethora of studies show that organizations face many
difficulties in integrating computerized systems into their work practices and
work processes.

Human Centered Systems may help reduce these usage problems; but people still
have to learn how to use them effectively, and organizations have to change
their training, design and reward practices (sometimes). Understanding what
kinds of "organizational learning" about HCS help leverage important value for
systems is a specially promising avenue. One promising avenue is to examine how
the creation of "communities of practice" among system developers and system
users can help people work with systems more effectively.

Another promising avenue is interdisciplinary teams -- examining both the
economic aspects of impacts on productivity, the sociological aspects of
changes in work practices, and the workflow and HCI dimensions of adjustment to
new technologies (among another approaches).

4.5 Technologically Facilitated Organizational Change

How do human-centered systems influence the ways that organizations can change
their ways of working, their products/services, and their relations with their
clients? To what extent do organizations have the "absorptive capacity"
effectively to use new (human-centered) computerized systems? What kinds of
openness to organizational change and technological changes are required to
effectively use human-centered systems.

These questions flow partly out of issues such as facing the productivity
paradox on a number of levels of organizational scale. We lack good empirical
studies of electronic spaces -- both workplaces and marketplaces -- and of
solid generalizable principles of the social dynamics of usage which could be
useful by computer scientists and designers. Ideally, we would develop
measurement tools and theoretical models which would speak to questions of
usability and impact in parallel with questions of design choices, market
feasibility, and high level requirements analysis. If an organization is
overly rigid, or is unable to make both the capital expenditure and the
investment in maintenance and training required for successful system
absorption, then early analysis of this state of affairs is both prudent and
important for the long term survival of the organization.

If effective systems use requires significant organizational learning, will
managers have the ability to admit having made mistakes? To what extent can
organizations create "open spaces" for their participants to discuss social and
technological options "freely?"

4.6 Modeling and Representing Human Centered Systems Use

Much of the claims about the likely roles of computers in organizations (and
communities, families, schools, etc.) involves making representations of:

* the computer system and how it is configured

* its relationship to other work practices and workplace technologies

* the work (or play or learning) involved

* the impact on organizational structure and social order.

These representations form a complex research program in their own right. How
can designers represent the contextual nature of knowledge informing both
design and use of systems? How can designers and implementers take account of
this information in their professional practice?

How can we develop research that is generalizable across various kinds of HCS
and the specific locales of their design/use? This is an old challenge in
social science. But with the advent of large scale networked computing, and the
pressing need for human centered approaches, opportunities for cooperation
across organizational analysis and systems design becomes more possible.

Understanding the knowledge and intent of others in the workplace is an
important aspect of human-centered systems development. People who use systems
also make representations about their own work and that of others. For example,
professionals are much more likely to share their knowledge in a forum, like a
LISTSERV if they expect praise rather than ridicule. They are more likely to
share information via documentary databases if they expect that their
co-workers will use their reports.

Most profoundly, we need ways to frame credible narratives or models of the use
and impact of information systems in specific organizational/social settings.
Most of the influential narratives in information and computer science are
centered on systems, information and their providers. We need a much better
understanding of the consumption-side of systems and information.

The state of research is that we have some specific studies of consumption of
specific information systems in specific settings. We need more such studies,
and also better ways to model the use/consumption of systems/information. In
particular, such models would have to help us take account of the multiple
work/home social worlds that people participate in.

The use of digital libraries to effectively enhance the quality of professional
communication is an area that is rich in possibilities for human-centered
approaches. There are questions about what it takes to incorporate the new
digital library technologies in the extant organizational infrastructure (the
recent firestorm about the new San Francisco Public Library can be read as
indicative of the strong public feelings over the issue). What does it take
to develop multiple media libraries -- where people locate, access and use
documents in paper or electronic forms? That is, given that people like books,
that libraries are more than repositories of bits (they are complex social and
community organizations), how can we conceive of human centered systems which
combine digital and other media? (Bishop and Star, 1996). After all, most
professionals print long report onto paper for careful reading and annotation,
even if they receive them in electronic forms (Kling and Covi, 1995; Levy and
Marshall 1995).

At the level of the digital document itself, the provenance and quality of
electronic documents are important social processes. "Junk on the web" is
partly a lag between the amount of information out there and the lack of good
indexing tools; but it is also partly a reflection of the lack of norms and
conventions developed for assessing electronic document quality and usefulness.
There are social processes of curatorship and adjudication, viz. the reluctance
of academics to publish electronically as "counting toward" tenure. We need,
in this sense, to understand documents in use, in a variety of organizational
and social contexts.

One aspect of this, which is common to many other research issues, is the
notion of material culture embodiment. Because digitization represents a shift
in the relationship of people and things (piles of paper, location of offices,
proximity of people to each other and to other physical resources), it is
important to develop good conceptual models of that shift. How does the stuff
around us fit in with information systems (or not)? What is the rich mixture
of electronic and non-electronic sources, in light of working, learning, and
leisure Note: leisure here does not just refer to the entertainment industry!
environments?

4.8 Standards Development Dynamics

Although past research has outlined the economic dynamics of technical
standards, these results remain largely theoretical. Qualitative research is
needed to understand these dynamics more concretely. In particular,
interdisciplinary research will be needed to comprehend the central role of
public relations and other forms of symbolic communication in the establishment
of standards. In an environment of network externalities, firms seeking to
establish new standards have a powerful incentive to gather allies and create
the impression that their standards are inevitable. Little is known, however,
about how this works in practice. Research is also needed to understand the
magnitude of these effects; it is still controversial, for example, under what
conditions, if any, a inferior technology can benefit from network effects
before being displaced by superior alternatives.

Susanne Bødker and Kaj Grønbaek, Users and designers in mutual
activity: An analysis of cooperative activities in systems design, in Yrjö
Engeström and David Middleton, eds, Cognition and Communication at Work,
Cambridge: Cambridge University Press, 1996.

Jewett, Tom and Rob Kling. 1991. "The Dynamics of Computerization Social
Science Research Team: A Case Study of Infrastructure, Strategies, and Skills."
Social Science Computer Review. 9(2)(Summer):246-275.

Steven G. Jones, Understanding community in the information age, in Steven

King, John L. and Kraemer, Kenneth L. (1981). "Cost as a Social Impact of
Telecommunications and Other Information Technologies." In Mitchell Moss
Telecommunications and Productivity, New York: Addison-Wesley.